34data/multilingual-synthetic-tts-es

multilingual-synthetic-tts-es

Mirror of the exact bmcore v24 holdout subset. Source: Reubencf/multilingual-synthetic-tts.

Local count agrees with published language count. Source card states reference-speaker consent and research/noncommercial use only; preserve restriction.

Contains 8000 synthetic audio files. This mirror repackages the media; it does not grant additional rights.

Source revision reviewed: 332a32ddb6ff09935516cf5bf24a7fb0a5ec066c.

Original source card

task_categories:

• —text-to-speech
• —automatic-speech-recognition language:
• —ja
• —de
• —ru
• —es
• —ko
• —pt
• —zh
• —en
• —fr size_categories:
• —10K<n<100K tags:
• —synthetic
• —voice-cloning
• —qwen3-tts
• —multilingual
• —tts pretty_name: Multilingual Synthetic TTS (Qwen3) ---

Multilingual Synthetic TTS Dataset

🏆 Submitted to the [Uncharted Data Challenge](https://www.adaptionlabs.ai/blog/the-uncharted-data-challenge) hosted by [Adaption Labs](https://www.adaptionlabs.ai) — credit to Adaptive Data by Adaption for organizing the hackathon.

A large-scale synthetic multilingual speech dataset — 68,677 clips across 9 languages, generated with Qwen3-TTS-12Hz-1.7B-Base using zero-shot voice cloning from 5 reference speakers.

Intended for training and evaluating TTS, ASR, voice conversion, and multilingual speech models. Each clip is paired with the ground-truth text and metadata (language, style, voice).

Dataset Summary

• —Total clips: 68,677
• —Languages: 9
• —Voices: 5 (zero-shot cloned)
• —Audio format: WAV, 12 kHz mono
• —Sentence source: LLM-generated prompts spanning conversational speech, informational/technical text, emotional utterances, and traditional proverbs

Languages

Styles

Styles cover a broad tonal range so the dataset is useful for both neutral TTS training and expressive voice work.

Voices

Each reference voice was used to speak sentences in every language — demonstrating Qwen3-TTS's cross-lingual voice-cloning capability.

Schema

Loading

from datasets import load_dataset

ds = load_dataset("Reubencf/multilingual-synthetic-tts", split="train")
print(ds[0])

# Filter by language
ja = ds.filter(lambda x: x["language"] == "ja")

# Iterate audio
for row in ds:
    wav = row["audio"]["array"]      # numpy float32
    sr  = row["audio"]["sampling_rate"]  # 12000
    txt = row["text"]

Generation Pipeline

1. 1.Sentence generation — topic-diverse prompts generated by gemini-flash-latest, covering conversational, informational, technical, emotional, and proverb-style utterances. Translated / localized per target language.
2. 2.Voice cloning synthesis — Qwen3-TTS-12Hz-1.7B-Base running on 2× H100 (multi-GPU spawn, batch size 32), with a rotating pool of reference speakers for cross-lingual cloning.
3. 3.Metadata — every clip is written alongside a manifest entry capturing language, style, voice, and sample rate.

Intended Uses

• —TTS training / fine-tuning — broad multilingual coverage with consistent speaker identities across languages.
• —ASR data augmentation — synthetic speech with noise-free transcripts.
• —Voice conversion / cloning research — each voice is represented across all supported languages, enabling cross-lingual speaker-identity studies.
• —Speech-LM evaluation — paired (text, audio) supervision in 9 languages.

Limitations

• —Synthetic voices: clones of a small reference pool — not demographically representative.
• —Single acoustic condition: clean, studio-like. No noise, reverb, or real-room artifacts.
• —Model-specific artifacts: occasional mis-pronunciations or prosody issues inherent to the TTS backbone.

License

Synthetic audio released for research and non-commercial use. Reference speakers consented to voice cloning for dataset creation. Users should comply with the Qwen3-TTS model license for downstream applications.

Citation

If you use this dataset, please cite:

@dataset{multilingual_synthetic_tts_2026,
  title  = {Multilingual Synthetic TTS (Qwen3)},
  author = {Fernandes, Reuben},
  year   = {2026},
  url    = {https://huggingface.co/datasets/Reubencf/multilingual-synthetic-tts}
}